SensitivityEstimator

class gammapy.estimators.SensitivityEstimator(spectrum=None, n_sigma=5.0, gamma_min=10, bkg_syst_fraction=0.05)

Bases: Estimator

Estimate sensitivity.

This class allows to determine for each reconstructed energy bin the flux associated to the number of gamma-ray events for which the significance is n_sigma, and being larger than gamma_min and bkg_sys percent larger than the number of background events in the ON region.

Parameters:

spectrumSpectralModel

Spectral model assumption. Default is Power Law with index 2.

n_sigmafloat, optional

Minimum significance. Default is 5.

gamma_minfloat, optional

Minimum number of gamma-rays. Default is 10.

bkg_syst_fractionfloat, optional

Fraction of background counts above which the number of gamma-rays is. Default is 0.05.

Examples

For a usage example see Point source sensitivity tutorial.

Attributes Summary

config_parameters	Configuration parameters.
selection_optional
tag

Methods Summary

copy()	Copy estimator.
estimate_min_e2dnde(excess, dataset)	Estimate dnde from a given minimum excess.
estimate_min_excess(dataset)	Estimate minimum excess to reach the given significance.
run(dataset)	Run the sensitivity estimation.

Attributes Documentation

config_parameters

Configuration parameters.

selection_optional

tag = 'SensitivityEstimator'

Methods Documentation

copy()

Copy estimator.

estimate_min_e2dnde(excess, dataset)

Estimate dnde from a given minimum excess.

Parameters:

excessRegionNDMap

Minimal excess.

datasetSpectrumDataset

Spectrum dataset.

Returns:

e2dndeQuantity

Minimal differential flux.

estimate_min_excess(dataset)

Estimate minimum excess to reach the given significance.

Parameters:

datasetSpectrumDataset

Spectrum dataset.

Returns:

excessRegionNDMap

Minimal excess.

run(dataset)

Run the sensitivity estimation.

Parameters:

datasetSpectrumDatasetOnOff

Dataset to compute sensitivity for.

Returns:

sensitivityTable

Sensitivity table.